The future is small: how startups drive innovation

Through forging better understanding of one another’s needs, pharma and innovative informatics startups can collaborate and use their strengths to achieve longer-term benefits for all.

Deloitte has been publishing its report ‘Measuring the return from pharmaceutical innovation’ yearly since 2010. The 2014 edition states that ‘pressure on research and development leaders to identify and successfully develop promising, innovative medicines is relentless’ – an observation which will come as no surprise to many.

The report focuses mainly on the identification of new targets, the creation of novel molecular structures and invention of platform technologies as the key innovation drivers to move the pipeline forward. However, it makes no mention of innovation in the information systems that make much of this possible and can hold the key to major behind-the-scenes improvements in R&D efficiency.

Innovation in this sense is not just about trying new third-party products, but actively mining public and private data for new insights, developing new algorithms, and experimenting with storage, memory, Central Processing Unit (CPU) and software configurations to experiment with data-based hypotheses in the same way as the chemists and biologists of the organisation plan for, and carry out, their experiments in the lab.

“The typical corporate R&D IT set-up does not necessarily lend itself well to change or experimentation”

Unfortunately, the typical corporate R&D IT set-up does not necessarily lend itself well to activities involving changes to, or experimentation with, IT resources. With strict change-control policies in place to manage procurement or prevent the disruption of production systems by runaway queries from rogue experimental software, and the difficulty of maintaining copies of massive datasets solely for experimental use, it can be difficult to obtain the resources required to carry out the type of exploration that many information scientists would like. Turning to the cloud may seem an obvious solution but here, too, many corporate IT policies prevent this. Information-based innovation can therefore be difficult to support within large established corporate IT environments.

Compare this with a typical informatics startup. With a real life-and-death need to succeed and the flexibility granted by an extremely lightweight IT policy, they are generally freer to create whatever systems they need to mine the data that drive their solutions. With no other distractions, such as running a manufacturing facility or maintaining a pipeline of new targets or molecules, they can concentrate solely on exploring new ideas and testing information hypotheses.

There are many thousands of such companies – often touting themselves as ‘big data experts’ in the current cycle of hype – and only a few will succeed but, while they survive, each has an opportunity to explore whatever it will and experiment freely until landing upon a perfect solution to take to market.

While keen to promote the concept of innovation, big pharma can sometimes be coy about acknowledging the parts of the R&D process that might benefit from a more innovative informatics-based approach. This makes it difficult for an informatics-based startup to assess the potential market for a new product or service. Reaching the right individuals within corporate organisations to gauge demand or negotiate access to suitable test data to support development is a long and complex process of socialisation and networking which not every startup founder can do.

Startups, while coming from a world of freedom with respect to corporate IT policy, need to have a better understanding of the impact of their solution on a production environment and how their product must be developed to operate safely and securely in a corporate setting. This will make them more attractive in initial discussions with prospective clients.

“Startups need to articulate the benefit of their product to the customer’s research productivity, product efficacy or sales targets”

They don’t necessarily have to have produced a corporate-friendly version of their software before demonstrating it, but they do need to make it clear at first contact that they understand the limitations and restrictions imposed by corporate IT environments and that their solution will be designed to respect that. Startups also need to ensure that they can clearly articulate the benefit of their product in terms of the impact it will have on the potential customer’s research productivity, product efficacy or sales targets, rather than focusing too much, at least initially, on the technical detail of how it works.

Pharma, for its part, needs to make it easier for potential partners in innovation projects to identify the true bottlenecks in R&D information systems. Some companies adopt the approach of ‘if you tell us your idea and we like it then we’ll try you out’, but don’t necessarily reciprocate with ‘if we tell you what we need and you can address that, then we’ll try you out’.

The distinction is subtle. The former encourages blue-sky thinking, the creation of ideas that are not at first based on any substantial market research or available information, but can deliver step-changes in productivity if they turn out to be right. The latter encourages the market to focus on addressing the real issues of today that can deliver immediate value and impact in the short term but not necessarily make a significant long-term difference.

It could be said that being more open with immediate needs on the part of big pharma might encourage startups to deliver revenue-generating products that address those issues faster, while simultaneously providing them with the financial breathing space that can support the development of their bigger, more impactful ideas.

Of course we all dream of that big idea that will change the world, but history shows that these sorts of innovations cannot be actively created or pursued. They tend to occur at opportune moments when the right circumstances appear at the right time to the right person (having a big idea is nearly always an individual thing, even if the process leading up to it was team-driven). Creating the environment that allows those eureka moments to happen is important and this is what the life sciences sector as a whole should be trying to achieve.

There are a number of organisations working to promote this kind of innovation-focused conversation between life science organisations. The Pistoia Alliance provides an environment where big pharma, startups, and all other organisations involved in the life science space can exchange ideas and discuss them as equals.

The best ideas are developed into working prototypes through member-funded projects that deliver and promote solutions that are as open as possible so that everyone can benefit from them. Project ideas are gathered from the whole community and range from the tactical, addressing immediate needs, through to the strategic, thinking about the long-term future and the disruptive solutions needed to make them reality.

A number of early-stage startups involved in Pistoia Alliance projects have now become established operations with their core business model built around the outcomes from the original projects, and a number of corporate members have benefitted from being exposed to these startups early on and adopting the resulting solutions ahead of the curve.

Other life science associations with a similar remit to the Pistoia Alliance are also actively encouraging collaboration for the greater good, including the Global Alliance for Genomics and Health, and Transcelerate. The Pistoia Alliance is currently working on a project to map out the landscape of associations in order to identify areas where greater cooperation may lead to increased benefits for all involved. Results from this research are expected later this year.

As the Deloitte report notes, ‘smaller companies appear to be developing assets more cost effectively and with better returns’ and ‘larger organisations would likely benefit from initiatives to simplify operating models and improve their ability to collaborate, to prioritise and accelerate development times’. So, working more closely with smaller startups through collaborative associations seems good advice for any corporate life sciences R&D IT executive.